Real-World Pitfalls and Strategies for Cloud BI

Cloud-based BI solutions enable government agencies to rapidly inject intelligence into any business problem at a fraction of the cost of traditional BI deployments. That means the ability to make faster, better informed business decisions.

But as the public sector's emphasis on cloud services has exploded, so has the noise level. Because it's one thing to talk about the benefits of moving critical functions like Business Intelligence or Analytics to the cloud, and another to understand the real-world options and pitfalls.

Complimentary Webinar for Government Executives and Technology Mangers. MicroStrategy and Qlarion--two companies at the forefront of providing BI solutions for government agencies--invite you to a complimentary webinar to discuss the myriad of potential challenges and the most effective strategies for cloud-based BI programs.

David Siegel, Blockchain, decentralization and business agility expert

Still confused about this whole Blockchain thing? Interested in investing in digital currencies, but not sure where to start? Want to get a better idea of the threats and opportunities?

David Siegel is a Blockchain, decentralization and business agility expert who has been a high-level management & strategy consultant to companies like Sony, Hewlett Packard, Amazon, NASA, Intel, and many start-ups. David has been praised for being able to explain Blockchain in the most simple and interesting way.

What you will learn:
-What is Bitcoin?
-What is the blockchain?
-What is Ethereum? What is Ether?
-What is a distributed application?
-What is a smart contract?
-What is a triple ledger?
-What about identity and security?
-What business models are at risk?
-What are the opportunities?
-What should we do?

Data visualization must be intuitive in order for non-IT business leaders to see data patterns. Representing data in a graphical or pictorial format is easy, but constructing the data in the best and most logical way can be tricky.

In this session, Umesh will talk about how to represent data simply to make quicker and better business decisions. He will walk through several data visualization techniques through business cases and examples. By the end of the session, you will not only know different data visualization techniques, but also have an understanding of circumstances under which each technique should be used and the best way to represent particular data sets for different business cases.

There has been a flood of publicity around big data, data processing, and the role of predictive analytics in businesses of the future.
As business operators how do we get access to these valuable business insights, even when there is not a data analyst around to walk us through their results?

- Should your software emulate a data scientist?
- Learn about the power of data visualizations.
- Learn about creating value from disperse data sets.

Predictive Analytics - everyone is talking about it and many organisations claim to be doing it. But are they? And what insights do they gain to then make tactical or strategic changes? How can analysts work with decision makers by sharing results in a visually effective and meaningful way while also informing them about possible courses of action?

This webinar is presented by Andy Kriebel, Head Coach at the Data School and Eva Murray, Tableau Evangelist at Exasol. Guest speakers on Predictive Analytics are Benedetta Tagliaferri, Consulting Analyst at The Information Lab and Matthew Reeve, Chief Data Wrangler at Exasol.

The webinar will look at some examples of predictive analysis and will show data visualization examples that are actionable and can drive further questions and discussions in an organisation.

Looking to take your graphs to the next level? Want to make sure you choose the right visualization? Plagued by the challenges of geospatial heat maps?

Get your questions ready and join this session where data experts Carl and Brett will go over the common questions they get asked and answer all the data visualization issues you've been plagued with, including how to:

-Use location-based data to put your visualization on the map
-Uncover new relationships, patterns and opportunities
-Identify emerging trends
-Answering comparative business questions with set analysis
-Understand best practices for creating an aesthetically-pleasing and useful visualization

When analysis needs to be used by decision makers that didn’t create it, the communication of the information and the message it conveys becomes critical. There is a plethora of ways to layout reports and dashboards, even within a single company.
Enter the SUCCESS formula, that “lightbulb” moment.

Introduced by the IBCS Association (International Business Communication Standards) the SUCCESS formula provides conceptual, perceptual and semantic rules that enable faster, better, and less-costly results in all stages of business communications and decision-making processes.

This webinar will introduce the 7 Rules of SUCCESS that provides a toolkit to aid analysts in designing their visualisations for better reach and decisions in their target audience.

The webinar will also introduce The Philips journey to implementing IBCS principles in their global "Accelerate!” Initiative.

Artificial intelligence has greatly changed the way we live since the 20th century. It involves the science and engineering of making machines intelligent and autonomous using computer programs.

The processing power of computers has been on the exponential increase with cost of processors and storage decreasing. This has made research and developments efforts in AI areas such as deep learning, once thought to be impossible possible.

In this webinar, we will examine current methods, application domains of specific methods, their impacts on our daily lives and try to answer questions on ethics of applying these technologies.

Artificial Intelligence (AI) is not a technology for the future; it’s a huge business opportunity for today. But how can your organisation become a trailblazer for AI innovation, transforming the way you work to deliver immediate – and lasting – bottom line value?

Former CERN scientist, Prof. Dr. Michael Feindt, is one of the brightest minds in Machine Learning. Join him for a 30-minute masterclass in how to apply AI to your business.

You’ll learn how AI can:
•Make sense of market and customer complexity, to deliver quick and effective decisions every single day
•Increase workforce productivity to improve output and staff morale
•Enhance decision-making and forecasting accuracy, for operational efficiency and improved productivity
•Be implemented into your business quickly, easily, with minimal disruption

Michael will also share real-life examples of how international businesses are using AI as a transformation tool, from his experience as founder of market-leading AI solution provider, Blue Yonder.

Analytics risks can keep you up at night. What if…
· We make a big investment and don’t break even?
· Management doesn’t trust the results?
· Analysts cross data privacy boundaries?

What a dilemma! You see the perils, yet you want the rewards that analytics can bring. The appropriate process enables you to dramatically reduce risks and maximize returns on your data and analytics investment.

In this presentation, you will learn:
· What causes most analytics failures
· How you can diminish risk and maximize returns through strong analytics process
· Why you (yes, you!) have a pivotal opportunity to establish high standards for analytics process right now

In an increasingly digitalised world, the value of information grows ever higher. Winning organisations – whether in financial services or any other vertical sector – will be those who can harness the power of data analytics to develop microscopic levels of insight and foresight into customer behaviours and operational activities in order to make progressive improvements on a continuous basis. Product development informed by factual evidence rather than educated guesswork, or real-time risk management based on a hyper-accurate picture of exposures, bring significant internal and external benefits.

However, while banks want to get closer to their customers, is the feeling mutual? Data privacy is a very sensitive issue, and the perception of what constitutes intrusion will likely vary between individuals. Institutions, therefore, need to walk a fine line between what’s genuinely useful and what’s genuinely creepy.

During this webinar, a panel of respected subject matter experts will discuss and dissect the key issues related to the widespread use of data analytics in financial services, identifying the obstacles which need to be overcome and the enablers that will drive FS forward successfully.

Personal data is a highly valuable asset. The winners of the future will be the organisations that make privacy intrinsic to data innovation. Join this webinar to learn how emerging best practices and technological solutions are helping financial institutions tackle data privacy in analytics and ML and drive commercial benefit.

Privitar is a leading privacy engineering software company. Privitar enables organisations to use, share and derive insight data safely. Privitar creates opportunities by allowing broader use of valuable information assets for collaboration and sharing, whilst reducing the risk associated with storing, processing and using sensitive data due to data breaches, regulatory penalties and the misuse of data.

Radiant is a robust tool for business analytics and running sophisticated models without any need for code development. It leverages the functions and tools in R and at the same time provides a user-friendly interface. With Radiant, you can manipulate and visualize your data, run different models from simple OLS to decision trees (CART) and neural networks, and evaluate your results.

The application is based on the Shiny package and can be run locally or on a server. Radiant was developed by Vicent Nijs. In this webinar, we review the tools available in Radiant and explain how easily you can use this tool without any setup or installation on your system.

Radiant key features:

• Explore: Quickly and easily summarize, visualize, and analyze your data
• Run different models: OLS, GLM, Neural Networks, Naïve Bayes and CART.
• Cross-platform: It runs in a browser on Windows, Mac, and Linux
• Reproducible: Recreate results and share work with others as a state-file or an Rmarkdown report
• Programming: Integrate Radiant's analysis functions with your own R-code
• Context: Data and examples focus on business applications

After this webinar you will learn:

• Data manipulation and running different models
• How to run advanced analytics in a browser on any device even in your tablet or iPad.

Presenter bio:

Ali has a Ph.D. in Finance from the University of Neuchatel in Switzerland and a BS in Electrical Engineering. He has extensive experience in financial modeling, quantitative modeling, and financial risk management in several US banks.

From automated vehicles to ride hailing apps, transportation as we know it is changing - and fast. But new technologies alone won't help communities build the efficient, equitable, and sustainable transportation networks communities want. In fact, these innovative technologies could do just the opposite, especially if they are not deployed wisely. Cities must collect the right data and enact the right policies to ensure they do not exacerbate problems like inequity and traffic, and to hold themselves accountable to the promise of new mobility technologies.

In this webinar, you will find out why - and how - the smartest cities of tomorrow will be those that adopt data-driven transportation strategies today. Join for Laura Schewel's presentation to gain insights into:

• Why the status quo for transportation data collection is no longer good enough
• The types of Massive Mobile Data that are useful for transportation and urban planning
• Algorithmic processing techniques that are critical for making this data useful
• Case studies from California and Virginia that demonstrate why Massive Mobile Data drives more effective transportation planning
• A forward-looking blueprint for using Massive Mobile Data to maximize the potential benefits of new transportation technologies - and minimize negative impacts

Laura Schewel founded StreetLight Data, a mobility analytics provider, after spending more than a decade as an advanced transportation researcher and statistician at the Rocky Mountain Institute and FERC. She has particular expertise in transportation systems, sustainability and safety, and vehicle/system modeling and analysis.

IoT is a technology that has the potential to make us healthy, wealthy, and wise especially in healthcare. Healthcare is just now adopting IoT to improve patient outcomes and decrease the cost of care.

In this webinar, you’ll learn:

- How to identify if an IoT solution will work for your use case.
- What others in healthcare are using IoT for.
- The challenges of IoT in healthcare

Whenever there is data, there is the chance to visualize it and gain valuable insights that can drive change and improvements. Governments have realized the potential that data holds for transforming our towns, cities, living spaces and communities to better address the needs of our modern society.

Governments may want to change public transport services to suit commuters who move away from city centers due to increasing living costs, or develop programs that deliver more support services to areas showing high incidences of mental illnesses, or simply monitor bike traffic to assess the necessity of additional cycle lanes and bike share programs in our capitals. Data and data visualization can help us identify the needs of our communities and can support us in addressing them effectively.

In this webinar Andy and Eva will present examples of Government using data to improve services for communities and will share how you can get involved through analyzing open data and becoming part of the wider 'dataviz' community.

We will examine challenges regarding business model design in the emerging context of the Internet of Things (IoT).
An unrefined IoT business model implies a significant risk in terms of investment and implementation.

Moving from A-B is slowly being revolutionised through data. Car-sharing and ride-hailing are just the beginning. Thousands of connected devices are currently monitoring data points, and although stand-alone analysis can be useful, true innovation occurs when these data sets are combined to transform into something new.

In the near future, IoT data explosion and the API revolution will collide to change city planning, urban movement and the role of the car in the 21st century.

First off, we set out to understand what big data means in the context of transportation, answering questions such as what is it, where is it coming from, and what can you do with it.
- Next, we'll zoom out and apply these learning to transport innovation in a wider context, considering how it will influence concepts such as urban movement, social mobility, and quality of life.
- Finally, we'll discuss the relationship between open data and innovation.

For decades “things” have been connected to the Internet. Embedded in carefully planned end-to-end solutions, the what and why of the data arising from these devices has often been hard-coded. In other words, in the M2M world, it is usually clear from the outset what is going to happen with the data. In a future IoT, this won’t necessarily be the case. In a world full of connected devices, the meaning and the potential of the device data is only going to become clear in the context where it is needed in.

But how can software tell that your connected thermometer is useful for a medical application, or that a car in the drive way is likely an indicator of your partner’s presence? This is where device catalogues, information models and ontologies come in handy.

While the talk is not specifically tailored towards a smart city focus, it should become clear how these technologies can be useful in such environment.